The heart contracts and relaxes with each heartbeat cycle. During contraction (systole), the heart ejects blood from the two ventricles. During relaxation (diastole), the ventricles refill with blood. Not all of the blood is emptied from the ventricles during systole. End of systole (ES) refers to the volume of blood remaining in the ventricles immediately after systole and before the beginning of diastole whereas ejection fraction refers to the percentage of blood which is pumped out of a filled ventricle during systole. End of diastole (ED) refers to the volume of blood held in the ventricles at the end of the refilling cycle.
X-ray left ventricular angiography is widely used for the assessment of cardiac functions by determining such parameters as ejection fraction, ED and ES. During this clinical check, patients undergo a cardiac catheterization procedure where X-ray opaque contrast dye is injected into left ventricle in order to visualize the left ventricle. The average acquisition time for the X-ray angiogram images is usually around 7 to 10 seconds, generating an X-ray image sequence with 150 to 400 frames.
In order to analyze the clinical parameters, an end-diastolic (ED) frame where the left ventricle is fully filled and an end-systolic (ES) frame where the left ventricle is maximally contracted have to be selected from the X-ray image sequence. After that, endocardial contours are segmented manually or automatically to determine the cross-sectional area of the projected left ventricle in the X-ray image frames, from which the ventricular volume in ED and ES can be estimated. The accuracy of the calculated ventricular volume depends on the accuracy of the ED and ES X-ray image frame selection.
Conventionally, ED and ES X-ray image frames are manually selected as the frames depicting the largest and smallest left ventricular area, respectively. This manual selection process is not only time consuming but also subject to human errors in visually selecting determining the ED and ES X-ray image frames. Automatic ED and ES frame selection is, thus, desirable for its potential to save clinicians' time and increase the selection accuracy.
However, because X-ray left ventricular images generally exhibit low contrast, noisy background, and dramatically changing left ventricular shape, accurate and dependable automatic method of selecting ED and ES frames has been elusive. The early efforts of computer aided left ventricular analysis has mainly focused on the contour segmentation of the X-ray images rather than ED and ES frame selection. Many approaches have been studied in the literature. Some have proposed an approach to the automated segmentation of X-ray left ventricular angiograms based on active appearance models and dynamic programming. Others have presented an algorithm for automated detection of the left ventricular's typical behaviors in cardiac radionuclide angiographs. These methods do not involve ED and ES image frame selection because of the difficulties in X-ray left ventricular image sequences as mentioned above.
Recently, developments have been made in ECG gated ED and ES frame selection to circumvent the severe image ambiguities in X-ray angiography by synchronizing the ECG signal with the X-ray image data. Such ECG gated methods, however, are not robust because unlike in a healthy patient, when a patient's ECG is pathological, it is difficult to indicate the correct ED and ES frames because the QR and T waves of the ECG signal do not have good correspondence with ED and ES. This fact greatly limits the application of such ECG-based approach as most patients undergoing left ventricular angiography have irregular ECG signal. Moreover, since such kind of approaches require strict synchronization between the ECG signal and the X-ray image data, the record delay or noise may introduce additional error and lead to wrong detection results. Accordingly, there is a need for an improved system and method for finding ED and ES frames in an angiography series.